Roughness-induced vehicle energy dissipation from crowdsourced smartphone measurements through random vibration theory
We propose, calibrate, and validate a crowdsourced approach for estimating power spectral density (PSD) of road roughness based on an inverse analysis of vertical acceleration measured by a smartphone mounted in an unknown position in a vehicle. Built upon random vibration analysis of a half-car mec...
| Main Authors: | , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Cambridge University Press
2020-01-01
|
| Series: | Data-Centric Engineering |
| Subjects: | |
| Online Access: | https://www.cambridge.org/core/product/identifier/S2632673620000179/type/journal_article |
| _version_ | 1811156476199174144 |
|---|---|
| author | Meshkat Botshekan Jacob Roxon Athikom Wanichkul Theemathas Chirananthavat Joy Chamoun Malik Ziq Bader Anini Naseem Daher Abdalkarim Awad Wasel Ghanem Mazdak Tootkaboni Arghavan Louhghalam Franz-Josef Ulm |
| author_facet | Meshkat Botshekan Jacob Roxon Athikom Wanichkul Theemathas Chirananthavat Joy Chamoun Malik Ziq Bader Anini Naseem Daher Abdalkarim Awad Wasel Ghanem Mazdak Tootkaboni Arghavan Louhghalam Franz-Josef Ulm |
| author_sort | Meshkat Botshekan |
| collection | DOAJ |
| description | We propose, calibrate, and validate a crowdsourced approach for estimating power spectral density (PSD) of road roughness based on an inverse analysis of vertical acceleration measured by a smartphone mounted in an unknown position in a vehicle. Built upon random vibration analysis of a half-car mechanistic model of roughness-induced pavement–vehicle interaction, the inverse analysis employs an L2 norm regularization to estimate ride quality metrics, such as the widely used International Roughness Index, from the acceleration PSD. Evoking the fluctuation–dissipation theorem of statistical physics, the inverse framework estimates the half-car dynamic vehicle properties and related excess fuel consumption. The method is validated against (a) laser-measured road roughness data for both inner city and highway road conditions and (b) road roughness data for the state of California. We also show that the phone position in the vehicle only marginally affects road roughness predictions, an important condition for crowdsourced capabilities of the proposed approach. |
| first_indexed | 2024-04-10T04:51:11Z |
| format | Article |
| id | doaj.art-165c90b18e814a83af20fe49e4a01eca |
| institution | Directory Open Access Journal |
| issn | 2632-6736 |
| language | English |
| last_indexed | 2024-04-10T04:51:11Z |
| publishDate | 2020-01-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | Data-Centric Engineering |
| spelling | doaj.art-165c90b18e814a83af20fe49e4a01eca2023-03-09T12:31:42ZengCambridge University PressData-Centric Engineering2632-67362020-01-01110.1017/dce.2020.17Roughness-induced vehicle energy dissipation from crowdsourced smartphone measurements through random vibration theoryMeshkat Botshekan0Jacob Roxon1Athikom Wanichkul2Theemathas Chirananthavat3Joy Chamoun4Malik Ziq5Bader Anini6Naseem Daher7Abdalkarim Awad8Wasel Ghanem9Mazdak Tootkaboni10Arghavan Louhghalam11Franz-Josef Ulm12https://orcid.org/0000-0002-7089-8069Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA Department of Civil and Environmental Engineering, University of Massachusetts, Dartmouth, Massachusetts 02747, USADepartment of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USADepartment of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USADepartment of Computer Science, University of Washington, Seattle, Washington 98115, USADepartment of Electrical and Computer Engineering, American University of Beirut, Beirut, LebanonDepartment of Electrical and Computer Engineering, Birzeit University, West Bank, PalestineDepartment of Electrical and Computer Engineering, Birzeit University, West Bank, PalestineDepartment of Electrical and Computer Engineering, American University of Beirut, Beirut, LebanonDepartment of Electrical and Computer Engineering, Birzeit University, West Bank, PalestineDepartment of Electrical and Computer Engineering, Birzeit University, West Bank, PalestineDepartment of Civil and Environmental Engineering, University of Massachusetts, Dartmouth, Massachusetts 02747, USADepartment of Civil and Environmental Engineering, University of Massachusetts, Dartmouth, Massachusetts 02747, USADepartment of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USAWe propose, calibrate, and validate a crowdsourced approach for estimating power spectral density (PSD) of road roughness based on an inverse analysis of vertical acceleration measured by a smartphone mounted in an unknown position in a vehicle. Built upon random vibration analysis of a half-car mechanistic model of roughness-induced pavement–vehicle interaction, the inverse analysis employs an L2 norm regularization to estimate ride quality metrics, such as the widely used International Roughness Index, from the acceleration PSD. Evoking the fluctuation–dissipation theorem of statistical physics, the inverse framework estimates the half-car dynamic vehicle properties and related excess fuel consumption. The method is validated against (a) laser-measured road roughness data for both inner city and highway road conditions and (b) road roughness data for the state of California. We also show that the phone position in the vehicle only marginally affects road roughness predictions, an important condition for crowdsourced capabilities of the proposed approach.https://www.cambridge.org/core/product/identifier/S2632673620000179/type/journal_articleInternational Roughness Indexinverse analysisrandom vibration theoryroad roughness metricsroughness-induced pavement–vehicle interactionsmartphone signal analysis |
| spellingShingle | Meshkat Botshekan Jacob Roxon Athikom Wanichkul Theemathas Chirananthavat Joy Chamoun Malik Ziq Bader Anini Naseem Daher Abdalkarim Awad Wasel Ghanem Mazdak Tootkaboni Arghavan Louhghalam Franz-Josef Ulm Roughness-induced vehicle energy dissipation from crowdsourced smartphone measurements through random vibration theory Data-Centric Engineering International Roughness Index inverse analysis random vibration theory road roughness metrics roughness-induced pavement–vehicle interaction smartphone signal analysis |
| title | Roughness-induced vehicle energy dissipation from crowdsourced smartphone measurements through random vibration theory |
| title_full | Roughness-induced vehicle energy dissipation from crowdsourced smartphone measurements through random vibration theory |
| title_fullStr | Roughness-induced vehicle energy dissipation from crowdsourced smartphone measurements through random vibration theory |
| title_full_unstemmed | Roughness-induced vehicle energy dissipation from crowdsourced smartphone measurements through random vibration theory |
| title_short | Roughness-induced vehicle energy dissipation from crowdsourced smartphone measurements through random vibration theory |
| title_sort | roughness induced vehicle energy dissipation from crowdsourced smartphone measurements through random vibration theory |
| topic | International Roughness Index inverse analysis random vibration theory road roughness metrics roughness-induced pavement–vehicle interaction smartphone signal analysis |
| url | https://www.cambridge.org/core/product/identifier/S2632673620000179/type/journal_article |
| work_keys_str_mv | AT meshkatbotshekan roughnessinducedvehicleenergydissipationfromcrowdsourcedsmartphonemeasurementsthroughrandomvibrationtheory AT jacobroxon roughnessinducedvehicleenergydissipationfromcrowdsourcedsmartphonemeasurementsthroughrandomvibrationtheory AT athikomwanichkul roughnessinducedvehicleenergydissipationfromcrowdsourcedsmartphonemeasurementsthroughrandomvibrationtheory AT theemathaschirananthavat roughnessinducedvehicleenergydissipationfromcrowdsourcedsmartphonemeasurementsthroughrandomvibrationtheory AT joychamoun roughnessinducedvehicleenergydissipationfromcrowdsourcedsmartphonemeasurementsthroughrandomvibrationtheory AT malikziq roughnessinducedvehicleenergydissipationfromcrowdsourcedsmartphonemeasurementsthroughrandomvibrationtheory AT baderanini roughnessinducedvehicleenergydissipationfromcrowdsourcedsmartphonemeasurementsthroughrandomvibrationtheory AT naseemdaher roughnessinducedvehicleenergydissipationfromcrowdsourcedsmartphonemeasurementsthroughrandomvibrationtheory AT abdalkarimawad roughnessinducedvehicleenergydissipationfromcrowdsourcedsmartphonemeasurementsthroughrandomvibrationtheory AT waselghanem roughnessinducedvehicleenergydissipationfromcrowdsourcedsmartphonemeasurementsthroughrandomvibrationtheory AT mazdaktootkaboni roughnessinducedvehicleenergydissipationfromcrowdsourcedsmartphonemeasurementsthroughrandomvibrationtheory AT arghavanlouhghalam roughnessinducedvehicleenergydissipationfromcrowdsourcedsmartphonemeasurementsthroughrandomvibrationtheory AT franzjosefulm roughnessinducedvehicleenergydissipationfromcrowdsourcedsmartphonemeasurementsthroughrandomvibrationtheory |